Digital Evolution

Evolution is not unique to biological life.

Darwin identified the requirements for evolution by natural selection: variation among individuals, heredity, and competition for survival. Biological life is one of the most well-known examples of an evolutionary process, but we can also study other examples of it. Analysis of other self-adapting systems can help us to understand and test fundamental tenets of evolutionary theory.

In previous work, we used Avida to understand how and why organisms evolve to be highly specialized - that is why they are highly adapted to perform certain functions, but less well adapted to perform others. This work revealed that the genetic overlap between selected and unselected traits is a good predictor of the probability that the latter will be maintained in environments where it experiences relaxed selection (Ostrowski et al. 2007). Experiments to disentangle genetically integrated traits showed that a trait can evolve counter to its phenotypic optimum owing to selection on a correlated trait. Moreover, selection on correlated traits can lead to alternative fitness peaks when populations evolve on rugged adaptive landscapes (Ostrowski et al. 2015). .

Above. The Avida world is populated with digital organisms. Each organism consists of a self-replicating computer program, but the copy process results in random mutations. Once the population reaches capacity, replication will replace an existing organism in the population. The organisms thus experience strong competition to replicate as quickly as possible - or face extinction. Strong competition for survival, coupled with heritable variation in traits that influence survival and reproduction, leads to adaptation.